Water quality impact of floating houses

A study of the effect on dissolved oxygen levels

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Abstract

The growing agglomeration and climate change are two challenges for the urban areas, which result in the reduction of permeable surface, the increase of surface runoff and a change in the temperature and precipitation patterns. These, in addition to the uncertainty of the climate change, point towards the need for adaptive sustainable solutions. Floating urbanisation is an old concept, which recently is gaining attention since it combines solutions for the above-mentioned problems. A number of aspects need to be investigated in order to move forward with the implementation of floating urbanisation. One of them is the possible effect on the water quality and ecology. Since water quality is a complex problem this thesis will focus on the effect of floating houses on Dissolved Oxygen levels. A small floating residence of six houses in the area of Delft will serve as a case study. In this area a measurement campaign in the months of July to September 2013 was conducted in order to collect data, which later served to assess the impact of the floating houses. The results from the field measurements were further evaluated by analysing which physical property or weather condition is responsible for the observed Dissolved Oxygen differences. Later on, a numerical model was developed in order to analyse in more detail the sources of these effects on Dissolved Oxygen. In particular the consequences of shadow and wind tunnel effect, induced by the floating houses, were studied. The results of the measurements and numerical simulations showed that there are differences on the Dissolved Oxygen levels in the upper part of the water column. The average measured differences are close to 10% (1mg/L), similar to the results obtained by the numerical models. Nevertheless, both of the floating houses effects (shadow and wind tunnel) are active on the same region of the water column, which makes it difficult to isolate their contributions. Further research and improvements on data collection and model development is recommended.